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Mixing AI and business

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This article is part of a blog series around Innovators Tribe: an event-driven platform that aims to empower companies to implement new technologies, and keep them ahead of the curve.

Do you know what your business will look like five years from now? Chances are that due to rapidly changing technologies, you can’t even picture what the impact will be one year from now. As recent studies show, using AI in business will be unavoidable for companies that want to stay relevant in their field. But while innovations in the fields of AI and machine learning are increasingly being implemented by large companies, it has also become more difficult to distinguish useful business solutions from techy buzzwords and hype.

AI will boost business

Results from a 2017 Accenture study show that AI technologies will increase productivity with 40% across 16 industries over the next 15-20 years. In another study of Capgemini’s Digital Transformation Institute, 73% of nearly a thousand interviewees said they believe  AI will boost their business by increasing customer satisfaction, while 65% said they believe it will prevent their customers from swaying to competitors. So why hasn’t there been a mass adoption of these technologies yet?

The reality is that there is often a lack of talent or know-how on how to implement new technology within a business framework. Companies need to define their problems before being able to identify which technological resources they need. One of the main difficulties then is setting up a data ecosystem and tools accordingly. The process of structurally implementing AI into your business may seem intimidating, but companies often overestimate the negative side effects. Learning to allocate primary sources to help ease the transition into business technologies of the future, may be a good first step.

Connection to academia

Leading innovators, scientists and high-tech startups can play a role in the process of identifying and solving business challenges. Ali Bahramisharif, former lead data scientist at Scyfer and co-founder of Machine2Learn, agrees that a connection to academia is critical for forward-thinking companies, as it offers direct access to innovative solutions and research results before even having been published. His new company provides support in finding new ways to manage data by using the latest developments in machine learning. He uses causality as an example, “a brand-new research field in computer science and a game-changer in extracting information from big data, as it targets the cause of a process”, Bahramisharif explains. “We are currently working on a general framework for extracting causality from large data sets which impact critical managerial decisions.”

In the future, the need for cross-disciplinary learning will grow, as more and more companies will have to implement technical innovations into their core business, or face higher chances of becoming obsolete. For companies that want to be ahead of the game, it is necessary to identify the right resources to become early adaptors. Access to leading research, and understanding its practical applicability has the transformational power for companies to gain a clear future outlook and prioritize the adoption of new technologies.

Innovators Tribe

Innovators Tribe provides a platform that makes it easy for companies to get such access. Activated through a series of events and workshops, Innovators Tribe brings together knowledge clusters around specific topics. From leading professors and researchers, to disruptive entrepreneurs and corporate front runners, all working together to solve challenges and change the future of business and AI.  The first event on AI & M2M has been planned for March 2018. Learn more.


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